Estimation of the Bivariate Survival Function with Generalized Bivariate Right Censored Data Structures
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Published 2004 in Advances in Survival Analysis, Chapter 8, pp. 143-175 (ed. N. Balakrishnan and C.R. Rao), Handbook of Statistics, 23, Elsevier North Holland.
Abstract:
We propose a bivariate survival function estimator for a general right censored data structure that includes a time dependent covariate process. Firstly, an initial estimator that generalizes Dabrowska's (1988) estimator is introduced. We obtain this estimator by a general methodology of constructing estimating functions in censored data models. The initial estimator is guaranteed to improve on Dabrowska's estimator and remains consistent and asymptotically linear under informative censoring schemes if the censoring mechanism is estimated consistently. We then construct an orthogonalized estimating function which results in a more robust and efficient estimator than our initial estimator. A simulation study demonstrates the performance of the proposed estimators.
Subject Area:
Statistical Theory and Methods, Survival Analysis
Suggested Citation:
Sunduz Keles, Mark J. van der Laan, and James M. Robins, "Estimation of the Bivariate Survival Function with Generalized Bivariate Right Censored Data Structures" (August 2002). U.C. Berkeley Division of Biostatistics Working Paper Series. Working Paper 109.
http://www.bepress.com/ucbbiostat/paper109